<i>Background</i>: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suitability for applications where there is a lack of a sufficient data set for the other classes. Infection incidence often brings prolonged ...

Background: Individuals with diabetes rely on medical equipment (eg, continuous glucose monitoring (CGM), hybrid closed-loop systems) and mobile applications to manage their condition, providing valuable data to health care providers. Data sharing from this equipment is regulated via Terms of Service (ToS) and Privacy Policy documents. The introduction of the Medical Devices Regulation (MDR) and In ...

Psycho-social factors are often addressed in behavioral health studies. While the purpose of many mHealth interventions is to facilitate behavior change, the focus is more prominently on the functionality and usability of the technology and less on the psycho-social factors that contribute to behavior change. Here we aim to identify the extent to which mHealth interventions for patient self- management ...

<p><i>Background</i>: When developing a mobile health app, users’ perception of the technology should preferably be evaluated. However, few standardized and validated questionnaires measuring acceptability are available.</p> <p><i>Objective</i>: The aim of this study was to assess the validity of the Norwegian version of the Service User Technology Acceptability Questionnaire (SUTAQ).</p> <p ...

Background: Today’s diabetes-oriented telemedicine systems can gather and analyze many parameters like blood glucose levels, carbohydrate intake, insulin doses, and physical activity levels (steps). Information collected can be presented to patients in a variety of graphical outputs. Despite the availability of several technical means, a large percentage of patients do not reach the goals established ...

Medical consultations for chronic diseases form an arena to provide information from health personnel to patients. This information is necessary for patients to understand how to deal with the possible lifelong symptoms and needed self-management activities. The amount of patient-generated health data is increasing. Today’s patients gather an increasing amount of personalised health-related information. ...

<b>Background:</b> The prevalence of diabetes and the use of electronic health (eHealth) resources are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be of great significance in this regard. However, little is known about the extent to which different kinds of eHealth tools are used, and how the use of eHealth is associated ...

The rapid improvement in mobile health technologies revolutionized what and how people can self-record and manage data. This massive amount of information accumulated by these technologies has potentially many applications beyond personal need, i.e. for public health. A challenge with collecting this data is to motivate people to share this data for the benefit of all. The purpose of this study is ...

Performing regular physical activity can be challenging. Integrating chatbots with social media platforms and physical activity sensors can potentially increase physical activity. The objective of this study was to identify design preferences for integrating an activity tracker supported chatbot in a social media platform. Norwegian adults (n=120) responded to an ad-hoc online survey. User preferences ...